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Jamba 1.5 Large vs Phi 4
Comprehensive side-by-side LLM comparison
Phi 4 leads with 19.7% higher average benchmark score. Jamba 1.5 Large offers 480.0K more tokens in context window than Phi 4. Phi 4 is $9.79 cheaper per million tokens. Overall, Phi 4 is the stronger choice for coding tasks.
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AI21 Labs
Jamba 1.5 Large is a language model developed by AI21 Labs. It achieves strong performance with an average score of 65.5% across 8 benchmarks. It excels particularly in ARC-C (93.0%), GSM8k (87.0%), MMLU (81.2%). It supports a 512K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents AI21 Labs's latest advancement in AI technology.
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Microsoft
Phi 4 is a language model developed by Microsoft. It achieves strong performance with an average score of 66.0% across 13 benchmarks. It excels particularly in MMLU (84.8%), HumanEval+ (82.8%), HumanEval (82.6%). The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
3 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
Phi 4
Microsoft
2024-12-12
Pricing Comparison
Cost per million tokens (USD)
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Jamba 1.5 Large
Input:$2.00
Output:$8.00
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Phi 4
Input:$0.07
Output:$0.14($9.79 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 17 common benchmarks
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Jamba 1.5 Large
Average Score:30.8%
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Phi 4
Average Score:50.5%(+19.7%)
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Knowledge Cutoff
Training data recency comparison
Jamba 1.5 Large
2024-03-05
Phi 4
2024-06-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Jamba 1.5 Large
2 providers
Bedrock
Throughput: 100 tok/s
Latency: 0.5ms
Throughput: 42 tok/s
Latency: 0.3ms
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Phi 4
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Jamba 1.5 Large
Avg Score:30.8%
Providers:2
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Phi 4
Avg Score:50.5%(+19.7%)
Providers:1